5 citations · 6 across the 4 of their papers we have counts for
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stat.ML2022
Modeling unknown dynamical systems with hidden parameters
Xiaohan Fu, Weize Mao, Lo-Bin Chang +1
We present a data-driven numerical approach for modeling unknown dynamical systems with missing/hidden parameters. The method is based on training a deep neural network (DNN) model…
stat.ML2020
Learning reduced systems via deep neural networks with memory
Xiaohan Fu, Lo-Bin Chang, Dongbin Xiu
We present a general numerical approach for constructing governing equations for unknown dynamical systems when only data on a subset of the state variables are available. The unkn…
stat.ML2018
Reducing Parameter Space for Neural Network Training
Tong Qin, Ling Zhou, Dongbin Xiu
For neural networks (NNs) with rectified linear unit (ReLU) or binary activation functions, we show that their training can be accomplished in a reduced parameter space. Specifical…